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Fix ddp tests + .test() #2512

Merged
merged 436 commits into from
Jul 7, 2020
Merged

Fix ddp tests + .test() #2512

merged 436 commits into from
Jul 7, 2020

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williamFalcon
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@pep8speaks
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pep8speaks commented Jul 5, 2020

Hello @williamFalcon! Thanks for updating this PR.

There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻

Comment last updated at 2020-07-07 16:09:33 UTC

@mergify mergify bot requested a review from a team July 5, 2020 11:53
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codecov bot commented Jul 5, 2020

Codecov Report

Merging #2512 into master will increase coverage by 1%.
The diff coverage is 82%.

@@           Coverage Diff           @@
##           master   #2512    +/-   ##
=======================================
+ Coverage      88%     90%    +1%     
=======================================
  Files          69      69            
  Lines        5629    5669    +40     
=======================================
+ Hits         4964    5077   +113     
+ Misses        665     592    -73     

@awaelchli awaelchli mentioned this pull request Jul 5, 2020
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@williamFalcon williamFalcon changed the title Tpu tests Fix ddp tests + .test() Jul 6, 2020
@@ -163,6 +165,10 @@ def train_fx(trial_hparams, cluster_manager, _):
else:
XLA_AVAILABLE = True

pid = os.getpid()
rng1 = np.random.RandomState(pid)
RANDOM_PORTS = rng1.randint(10000, 19999, 100)
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does this cause a failure for a distributed cluster > 100 nodes?

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the random_port thing is only used in non-multi node ddp.

torch.cuda.empty_cache()

if self.global_rank == 0 and q is not None:
q.put(self.checkpoint_callback.best_model_path)
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this feels hacky, what are we trying to do here? return the state of a callback to the main node? why put this specific attribute in the queue?

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@awaelchli awaelchli Jul 7, 2020

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I think he did this so that one can call .test in the main process, which will access the best model to test on. But I agree with you, this seems fragile and dangerous to modify state across processes, there's gotta be a better way. Could one put the whole trainer in the queue in theory?

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i tried that but it didn’t work. i think in a different PR we can do something like state_dict for the trainer.

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i agree this isn't optimal but let's get a release that fixes all the test issues (which this PR does) and then we can figure out a longer term strategy

pytorch_lightning/trainer/trainer.py Outdated Show resolved Hide resolved
@mergify mergify bot requested a review from a team July 7, 2020 02:24
@Borda Borda self-requested a review July 7, 2020 05:43
@Borda Borda added bug Something isn't working priority: 0 High priority task labels Jul 7, 2020
@Borda Borda added this to the 0.8.x milestone Jul 7, 2020
@@ -22,7 +22,7 @@ def wrapped_fn(*args, **kwargs):


def _warn(*args, **kwargs):
warnings.warn(*args, **kwargs)
warnings.warn(UserWarning(*args, **kwargs))
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this causes the failing test on deprecation warnings, @williamFalcon

@mergify mergify bot requested a review from a team July 7, 2020 06:41
@@ -377,17 +384,18 @@ def set_nvidia_flags(self, is_slurm_managing_tasks, data_parallel_device_ids):
# don't make this debug... this is good UX
rank_zero_info(f'CUDA_VISIBLE_DEVICES: [{os.environ["CUDA_VISIBLE_DEVICES"]}]')

def set_random_port(self):
def set_random_port(self, force=False):
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@jeremyjordan this function is only ever called from ddp on a single node... not distributed

rng1 = np.random.RandomState(pid)
default_port = rng1.randint(10000, 19999, 1)[0]
# pick a random port first
assert self.num_nodes == 1, 'random port can only be called from single node training'
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@jeremyjordan added this to make sure it's used as expected

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I'm understanding this, it looks like this will disable multi-node support (at least, I'm not able to run across multiple nodes anymore due to this assertion - see issue here: flatironinstitute/deepblast#46)

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@mortonjt can you open a github issue about this and explain how you launched your script?

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Sure thing. See #2578

@@ -446,15 +455,24 @@ def spawn_ddp_children(self, model):
sleep(delay)

local_rank = 0
self.ddp_train(local_rank, model, is_master=True)
results = self.ddp_train(local_rank, q=None, model=model, is_master=True)
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rather longer var name the q

@mergify mergify bot requested a review from a team July 7, 2020 15:33
@williamFalcon
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@tgaddair hey! any chance you can look at this?

@williamFalcon williamFalcon merged commit 11069c8 into master Jul 7, 2020
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tgaddair commented Jul 7, 2020

Hey @williamFalcon, what was the issue? I see this PR has been merged. Is there still something that needs to be fixed on the Horovod side for this?

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awaelchli commented Jul 7, 2020

I don't think this is Horovod's fault. Something witht the checkpoint paths changed. The tests are now simply skipped, which is not good :(
I will try to fix it in #2514 wish me luck :)

@williamFalcon
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perfect! @awaelchli .
@tgaddair looks like it's on our end. All good! thanks for taking a look though


assert event_acc.summary_metadata['_hparams_/experiment'].plugin_data.plugin_name == 'hparams'
assert event_acc.summary_metadata['_hparams_/experiment'].plugin_data.content == hparams_data
#
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add TODO

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I added a reminder in the related issue #2371 that we should fix this

@mergify mergify bot requested a review from a team July 7, 2020 17:00
@@ -88,6 +88,7 @@ def test_horovod_cpu_implicit(tmpdir):
_run_horovod(trainer_options)


@pytest.mark.skipif(True, reason="fix hv")
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just @pytest.mark.skip(reason="fix hv")

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@Borda I removed it again in #2514 :)

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7 participants